code: def from_json(self, data_json):
      self.scale = preprocessing.StandardScaler(
          copy=True, with_mean=True, with_std=True
      )
      self.scale.scale_ = data_json.get("scale")
      if self.scale.scale_ is not None:
          self.scale.scale_ = np.array(self.scale.scale_)
      self.scale.mean_ = data_json.get("mean")
      if self.scale.mean_ is not None:
          self.scale.mean_ = np.array(self.scale.mean_)
      self.scale.var_ = data_json.get("var")
      if self.scale.var_ is not None:
          self.scale.var_ = np.array(self.scale.var_)
      self.scale.n_samples_seen_ = int(data_json.get("n_samples_seen"))
      self.scale.n_features_in_ = int(data_json.get("n_features_in"))
      self.columns = data_json.get("columns", [])
      self.scale_method = data_json.get("scale_method")
      self.X_min_values = data_json.get("X_min_values")
      if self.X_min_values is not None:
          self.X_min_values = np.array(self.X_min_values)
  
file_path: mljar-supervised/supervised/preprocessing/scale.py
imports: import numpy
  import pandas
  from sklearn import preprocessing
label_desc: Use image node_id 6 for calling the Scale obj's underlying member method code with example usage: obj.from_json(data_json) without return types